Distinguished Engineer, Production Engineering, Cluster Management

NVIDIA is seeking a Distinguished Engineer for its Production Engineering organization to lead cluster management for DGX Cloud GPU capacity. The role defines technical strategy, architectural direction, operating standards, automation, and cross-organizational processes that ensure DGX Cloud clusters are reliable, scalable, supportable, and production-ready across on-premises, hyperscaler, and cloud partner environments.

Responsibilities:

• Define the long-range technical strategy for operating DGX Cloud clusters consistently across local data centers, hyperscalers, and NeoCloud environments
• Define the architectural direction and fundamental operating standards for cluster lifecycle, runtime delivery, restoration, release readiness, and steady-state operability concerning DGX Cloud capacity
• Guide the roadmap and execution of critical cross-organizational investments that improve production readiness, operational safety, performance, and cross-team coordination
• Make and influence high-impact technical decisions that build how platform, hardware, provider, and service teams work together to operate DGX Cloud resources in production
• Build durable workflows, interfaces, and engineering handshakes across Kubernetes production service, provider and hardware preparation, on-prem and bare-metal
• Restructure operations, and service-layer reliability domains
• Build and evolve the automation, APIs, operating workflows, and readiness gates required to move new capacity into stable production and keep existing capacity balanced
• Implement production operating approaches that lower manual input, establish clear ownership responsibilities, and increase consistency, traceability, and release safety within DGX Cloud environments
• Partner closely with platform teams, hardware and provider engineering, service owners, and other Production Engineering leaders to identify repeated friction and convert it into durable improvements in software, processes, and operational interfaces
• Raise the engineering bar for operability, resilience, scalability, and performance across cluster operations through build leadership, architecture review, and technical standards

Requirements:

• BS, MS, or PhD in Computer Science, Electrical Engineering, or a related technical field, or equivalent experience
• 18+ years of experience building and operating large-scale distributed systems, infrastructure platforms, or production environments
• Confirmed company-level technical leadership at principal, distinguished, or equivalent scope in production engineering, SRE, infrastructure software, or cloud platforms
• Consistent track record of defining operating models, architectural direction, and engineering standards across multiple technical domains and organizations
• Consistent record leading large, cross-team technical efforts from concept through production, including aligning collaborators, navigating for clarity and delivering measurable outcomes
• Deep experience with one or more of these areas: Kubernetes-based production systems, infrastructure automation, or distributed systems operations
• Strong software engineering skills in languages such as Python, Go, or similar low-level programming languages
• Deep understanding of distributed systems, Linux, networking, containers, and production reliability concerns
• Experience crafting operational workflows, APIs, service interfaces, or automation frameworks that become the standard way teams run production systems
• Strong architectural judgment and a validated history of simplifying complex operational problems through reusable software, clear technical strategy, and durable engineering direction
• Defined the structural foundation for a large, heterogeneous infrastructure environment spanning multiple platforms or providers
• Established widely used operating standards, architectures, APIs, or workflows that improved reliability, operability, or performance at company scale
• Built automation and engineering interfaces that connect platform teams, infrastructure teams, and service owners into a consistent production system
• Experience improving production readiness, restoration, runtime safety, or release quality for large-scale infrastructure
• Equally comfortable setting technical strategy, reviewing architecture at scale, writing code, and driving adoption across organizational boundaries